Yacht energy storage battery internal short circuit detection method, device, equipment and medium

Abstract

The invention relates to the technical field of energy storage batteries, and discloses a yacht energy storage battery internal short circuit detection method, device and equipment and a medium, and the method comprises the steps: sampling the voltage and current of a yacht energy storage battery pack, and obtaining original sampling data; performing parameter identification to obtain RC network dynamic response data; performing sliding window Fourier transform and wavelet packet decomposition to obtain a target feature vector; performing voltage abrupt change feature judgment, current abrupt change feature judgment and impedance spectrum feature judgment based on the target feature vector to obtain a multi-stage fault judgment result; starting the three-ring nested control structure and inputting the three-ring nested control structure into a PWM modulation unit to obtain a control compensation signal; the control compensation signal is input into the current sharing controller, the PWM duty ratio of the parallel branches is adjusted, and a current sharing control signal is obtained, the reliability of fault detection is improved, cooperative control of state protection, power balance and current tracking is achieved, and the current distribution problem of the parallel branches is effectively solved.

Description

Technical Field

[0001] The present invention relates to the technical field of energy storage batteries, and in particular to a method, device, equipment and medium for detecting internal short circuits in yacht energy storage batteries. Background Art

[0002] The yacht energy storage battery system is the core component of the yacht's electric propulsion, and its safety and reliability directly affect the yacht's navigation safety. With the development of the trend of yacht electrification, the series-parallel structure of large-capacity energy storage battery packs has become increasingly complex, and the risk of internal short-circuit failures has increased significantly. Traditional short-circuit detection methods mainly rely on voltage and current threshold judgments, but in marine environments, due to the influence of factors such as temperature and humidity, misjudgments and missed judgments are prone to occur. In addition, the frequent start-stop transitions and changes in navigation conditions of the yacht energy storage system make it difficult to accurately extract short-circuit fault characteristics.

[0003] The yacht energy storage battery pack operates for a long time in the marine environment, and its internal materials are prone to aging and corrosion, resulting in an increased risk of local short circuits. Current short circuit detection technology generally uses a single frequency domain feature analysis method, such as fast Fourier transform or continuous wavelet transform, but these methods have large differences in detection accuracy under different working conditions. Especially when the yacht is sailing at high speed, the dynamic response characteristics of the battery pack change dramatically, and traditional detection methods are difficult to meet real-time monitoring needs. Summary of the invention

[0004] The present invention provides a method, device, equipment and medium for detecting internal short circuit of a yacht energy storage battery. The present invention improves the reliability of fault detection, realizes coordinated control of state protection, power balance and current tracking, and effectively solves the current distribution problem of parallel branches.

[0005] In a first aspect, the present invention provides a method for detecting an internal short circuit of a yacht energy storage battery, the method comprising: Sample the voltage and current of the yacht energy storage battery pack to obtain original sampling data; Inputting the original sampling data into a three-level RC parallel network model for parameter identification to obtain RC network dynamic response data; Performing sliding window Fourier transform and wavelet packet decomposition on the RC network dynamic response data and the original sampling data to obtain a target feature vector; Based on the target feature vector, voltage mutation feature judgment, current mutation feature judgment and impedance spectrum feature judgment are performed to obtain a multi-level fault judgment result; A three-loop nested control structure is started according to the multi-level fault judgment result, and the calculation results of the current tracking control, the power balance control and the state protection control are input into the PWM modulation unit to obtain a control compensation signal; The control compensation signal is input into the current sharing controller to adjust the PWM duty cycle of the parallel branch to obtain a current sharing control signal.

[0006] In a second aspect, the present invention provides a yacht energy storage battery internal short circuit detection device, the yacht energy storage battery internal short circuit detection device comprising: The sampling module is used to sample the voltage and current of the yacht energy storage battery pack to obtain the original sampling data; A parameter identification module, used for inputting the original sampling data into a three-level RC parallel network model for parameter identification to obtain RC network dynamic response data; A decomposition module, used for performing sliding window Fourier transform and wavelet packet decomposition on the RC network dynamic response data and the original sampling data to obtain a target feature vector; A judgment module, used to perform voltage mutation feature judgment, current mutation feature judgment and impedance spectrum feature judgment based on the target feature vector to obtain a multi-level fault judgment result; A control compensation module, used to start a three-loop nested control structure according to the multi-level fault judgment result, input the calculation results of current tracking control, power balance control and state protection control into a PWM modulation unit, and obtain a control compensation signal; The current sharing control module is used to input the control compensation signal into the current sharing controller, adjust the PWM duty cycle of the parallel branch, and obtain the current sharing control signal.

[0007] A third aspect of the present invention provides a computer device, comprising: a memory and at least one processor, wherein the memory stores instructions; the at least one processor calls the instructions in the memory so that the computer device executes the above-mentioned method for detecting internal short circuit of a yacht energy storage battery.

[0008] A fourth aspect of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores instructions, which, when executed on a computer, enable the computer to execute the above-mentioned method for detecting internal short circuits of yacht energy storage batteries.

[0009] In the technical solution provided by the present invention, by adopting a three-level RC parallel network model and combining it with the correction of marine environmental parameters, the dynamic characteristics of yacht energy storage batteries under different working conditions are accurately described; by combining the sliding window Fourier transform and wavelet packet decomposition, multi-scale feature extraction is realized, and the integrity of feature information is enhanced; a three-level judgment mechanism based on voltage mutation, current mutation and impedance spectrum is designed, and hysteresis comparison processing is introduced to improve the reliability of fault detection; a three-loop nested control structure is proposed to realize the coordinated control of state protection, power balance and current tracking, and ensure the stability of system output; based on the master-slave current sharing control strategy, the current distribution problem of the parallel branch is effectively solved, and the dynamic response capability of the system is improved. The present invention enhances the safety and reliability of the system through the coordinated cooperation of multi-level protection and control strategies. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0011] Figure 1 A schematic diagram of the steps of a method for detecting an internal short circuit of a yacht energy storage battery in an embodiment of the present invention; Figure 2 This is a schematic diagram of the structure of a device for detecting internal short circuit of a yacht energy storage battery in an embodiment of the present invention; Figure 3 It is a schematic block diagram of the structure of a computer device in an embodiment of the present invention. DETAILED DESCRIPTION

[0012] The embodiments of the present invention provide a method, device, equipment and medium for detecting internal short circuit of a yacht energy storage battery. The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "including" or "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0013] For ease of understanding, the specific process of the embodiment of the present invention is described below. Figure 1 , an embodiment of the method for detecting internal short circuit of a yacht energy storage battery in an embodiment of the present invention includes: Step S1, sampling the voltage and current of the yacht energy storage battery pack to obtain original sampling data; It is understandable that the execution subject of the present invention may be a yacht energy storage battery internal short circuit detection device, or a terminal or a server, which is not specifically limited here. The embodiment of the present invention is described by taking a server as an execution subject as an example.

[0014] Specifically, the voltage and current of the yacht energy storage battery pack are sampled with high precision, wherein the sampling channel of the voltage acquisition unit is differentially amplified to improve the anti-interference ability of the signal and ensure the accuracy of the signal. In this process, the voltage signal of the sampling channel is amplified by a high-precision instrument amplifier, and the input signal is corrected by a precision resistor network to ensure that the sampled voltage signal is not affected by external interference sources. After amplification, the voltage acquisition gain coefficient is obtained, and the gain coefficient is used to compensate for the error in the sampling circuit to make the sampling data more accurate. The voltage acquisition gain coefficient is input into the voltage sampling circuit to perform high-precision sampling of the voltages of multiple series-connected battery cells in the yacht energy storage battery pack. The sampling process uses a 16-bit precision ADC to ensure that the voltage measurement result has sufficient resolution and accuracy. At the same time, the output signal of the Hall sensor in the current acquisition unit is operationally amplified, and the signal is enhanced by a high-gain operational amplifier, and the high-frequency noise is eliminated by a filter to obtain the current acquisition gain coefficient, and the current acquisition gain coefficient is input into the current sampling circuit to perform current sampling on the two parallel branches of the yacht energy storage battery pack. The sampling process also uses a 16-bit precision ADC to ensure high precision and high resolution of current measurement. When sampling the current signal, temperature compensation and signal filtering are performed to obtain current sampling data. The sampled data is converted by ADC. The sampled voltage and current data are converted into digital data through a 12-bit ADC, and the analog signal is converted into a data format that can be calculated and analyzed by a digital signal processor (DSP), so that the subsequent short-circuit detection algorithm can process and analyze the data. In order to ensure the stability and real-time performance of data transmission, the converted digital sampled data is transmitted to the digital signal processor via the CAN bus. During the data transmission process, the CAN bus supports multi-node communication and allows the system to maintain high-reliability data transmission in a complex electrical environment, avoiding data damage or loss caused by transmission errors. After receiving the data, the digital signal processor verifies the sampled data to ensure the integrity and accuracy of the data. The verification process uses methods such as CRC (cyclic redundancy check) or parity check to verify whether there is an error in the data transmission process, and retransmits the data when necessary to improve the reliability of the data. The data after verification is used as the original sampled data for subsequent short-circuit detection algorithm analysis.

[0015] Step S2, inputting the original sampling data into the three-level RC parallel network model for parameter identification to obtain the RC network dynamic response data; Specifically, the impact of the marine environment on battery performance is considered. Since the marine environment has large temperature and humidity fluctuations, these factors will affect the internal resistance, polarization characteristics and charge and discharge efficiency of the battery. The original sampled data is corrected by the marine environment parameters to ensure the calculation accuracy of the RC model. In this process, the original sampled data is corrected based on the temperature coefficient and humidity coefficient. By establishing relationship models such as temperature-impedance, humidity-leakage current, the voltage and current sampling data of the battery are corrected to obtain environmental correction data. The correction process uses nonlinear interpolation or data fitting methods to ensure that the corrected data can accurately reflect the actual working state of the battery. The environmental correction data is input into a three-level RC parallel network model, which is used to characterize the dynamic response characteristics of the battery. Among them, different branches of the three-level RC network correspond to different yacht working conditions, so appropriate time constants are set according to different working modes. The time constant of the fast charge and discharge response branch is set to the first target value, which is used to describe short-term high-power charge and discharge processes, such as acceleration or sudden load changes of yachts. The time constant of the start-stop transition branch is set to the second target value, which is used to describe the energy change characteristics when the yacht starts or stops, usually involving large current changes. The time constant of the navigation steady-state branch is set to the third target value, which reflects the steady-state charge and discharge characteristics of the battery during the stable navigation of the yacht. The parameters of the yacht working condition RC branch are discretized to facilitate subsequent numerical calculation and real-time control. In the discretization process, the state space expression is adopted, and the capacitor voltage and temperature state of the three-level RC parallel network model are used as state variables to establish an extended discrete state equation. This equation can describe the dynamic behavior of the battery and perform numerical calculations at different time steps, so that the system can adapt to different sampling cycles and calculation accuracy requirements. Since the dynamic response of the battery is greatly affected by temperature, humidity and load changes, these environmental factors are introduced into the discrete state equation and corrected by an adaptive algorithm. In order to improve the adaptability of the model, the response data of the battery pack under different temperature, humidity and load conditions are calculated by the least squares method according to the extended discrete state equation to obtain the environmental adaptive parameter matrix. The least squares calculation solves the model parameters through the optimal fitting method, so that the prediction results of the model can be as close to the actual observed data as possible. The calculation adopts the recursive least squares or Kalman filtering method to ensure the stability and convergence of the parameter estimation. The environmental adaptive parameter matrix enables the RC network model to dynamically adjust its own parameters to adapt to different marine environmental conditions. Multivariate correlation calculations are performed on the environmental adaptive parameter matrix to establish a mapping relationship between RC parameters and temperature, humidity, and state of charge (SOC). This mapping relationship is used to describe the changing rules of RC parameters under different environmental conditions. For example, an increase in temperature leads to a decrease in the internal resistance of the battery, while an increase in humidity leads to an increase in the leakage current of the battery.The RC parameter correction model is constructed by multivariate regression or machine learning methods, and is trained using an environmental adaptive parameter matrix to obtain more accurate RC parameter correction values. The RC parameter correction values ​​are updated to the extended discrete state equation for numerical calculation to obtain the RC network dynamic response data. The numerical calculation uses the Euler method or the Runge-Kutta method to ensure the stability and accuracy of the calculation. During the calculation process, the corrected RC parameters are used to calculate the transient and steady-state responses of the battery, and are used in the subsequent short-circuit detection algorithm.

[0016] Step S3, performing sliding window Fourier transform and wavelet packet decomposition on the RC network dynamic response data and the original sampling data to obtain a target feature vector; Specifically, the RC network dynamic response data and the original sampling data are processed by sliding windows to eliminate the non-stationarity of the data in the time domain. In the process of sliding window processing, overlapping window technology is used to avoid signal distortion caused by window boundary effects, and the selection of window length needs to be optimized in combination with the dynamic characteristics of the yacht energy storage battery so that it can capture short-term transient characteristics and retain long-term trend information. After completing the sliding window processing, the data is subjected to spectrum leakage suppression processing to reduce the spectrum expansion problem caused by the limited sampling time and obtain the spectrum leakage-free data. By adding a window function, such as a Hanning window or a Kaiser window, the high-frequency interference caused by spectrum leakage is suppressed to make the spectrum characteristics of the signal clearer. The spectrum leakage-free data is input into a second-order Butterworth low-pass filter. Due to its maximum flat amplitude-frequency response characteristics, the Butterworth filter can effectively remove high-frequency noise without introducing large phase distortion, so that the filtered signal can retain the original dynamic characteristics. In this step, the cutoff frequency of the second-order filter is optimized and set according to the operating frequency range of the energy storage battery, and is set at the upper limit of the short-circuit characteristic frequency to ensure that key fault information is not filtered out. The signal after low-pass filtering is the preprocessed signal data. The preprocessed signal data is subjected to a fast Fourier transform operation to convert the signal from the time domain to the frequency domain and extract the frequency characteristics of the signal. Fast Fourier transform (FFT) can efficiently calculate the spectral information of the signal. Especially when a battery short circuit fault occurs, due to the change in equivalent resistance, the dynamic response signal of the battery will change significantly within a specific frequency range. The frequency domain characteristic data of the battery short circuit fault is obtained through FFT analysis. During the FFT calculation process, in order to avoid the influence of aliasing, the sampling frequency is ensured to meet the Nyquist sampling theorem, and the amplitude is normalized after the spectrum calculation to improve the stability of feature extraction. The phase difference between adjacent characteristic frequency points is calculated according to the frequency domain characteristic data to obtain the phase difference characteristic data. During the calculation process, the phase information of the frequency domain signal is extracted, and then the phase change between adjacent frequency points is calculated by the differential method, and the phase mutation threshold is set in combination with the short circuit characteristic frequency range, so as to screen out the phase difference characteristic data related to the short circuit fault. At the same time, the preprocessed signal data is decomposed by wavelet packets to extract the time-frequency characteristics of the signal. Wavelet packet decomposition is a multi-scale analysis method that decomposes the signal into different frequency bands to obtain more detailed energy distribution information. In the specific implementation process, a suitable wavelet basis function, such as Daubechies wavelet, is selected to ensure the stability and computational efficiency of the decomposition. Then the signal is multi-layered and the energy distribution of each frequency band is calculated to obtain the wavelet energy feature data. Vector mapping is performed on the frequency domain feature data, phase difference feature data, and wavelet energy feature data to unify different types of feature data.In the process of vector mapping, different features are normalized to eliminate the order of magnitude differences between different features, and the data distribution is adjusted using a standardized method to satisfy the normal distribution assumption and improve the effect of subsequent data fusion. Feature selection is performed on the normalized feature data to eliminate redundant information and improve the effectiveness of the feature data. Vector fusion is performed on the mapped feature data to form the final target feature vector.

[0017] Step S4, performing voltage mutation feature judgment, current mutation feature judgment and impedance spectrum feature judgment based on the target feature vector to obtain a multi-level fault judgment result; Specifically, the target feature vector is vector demapped to obtain the data of each feature component. The inverse mapping function is used to decompose the fused feature vector into its independent feature components for subsequent analysis and calculation. Feature alignment is performed during the demapping process to ensure that the feature component data extracted from the target feature vector remains consistent in time and frequency scales, thereby ensuring the accuracy of the analysis. The voltage drop is calculated for the frequency domain features in the feature component data to determine the voltage mutation feature judgment result. When a short circuit fault occurs, the reduction of the equivalent impedance inside the battery will cause the terminal voltage to drop significantly. By calculating the drop change of the voltage signal within a specific frequency range, it is determined whether there is a short circuit fault. The voltage drop calculation method uses amplitude difference calculation, that is, the voltage spectrum amplitude within a specific time window is calculated, and the voltage mutation threshold is set for judgment. If the calculated voltage drop exceeds the set threshold, it is determined that there is a possibility of a short circuit fault. In order to improve the accuracy of the calculation, while calculating the voltage drop, the signal is detrended to eliminate the influence of the voltage change trend on the long time scale on the calculation result. According to the voltage feature judgment result, the current slope is calculated for the frequency domain features in the characteristic component data to obtain the current feature judgment result. Since the current signal will show a steep rise when a short circuit fault occurs, the severity of the short circuit fault is judged by calculating the transient change rate of the current signal. The method for calculating the current slope adopts the method of numerical differentiation, that is, the change rate of the current signal in a short time window is calculated, and the current mutation threshold is combined for judgment. If the calculated current slope exceeds the preset threshold, it indicates that a serious short circuit fault has occurred in the system. Since a short circuit fault may cause high-frequency oscillation of the current signal, the signal needs to be smoothed when calculating the current slope to remove the influence of high-frequency noise and improve the stability of the calculation. At the same time, in order to verify the occurrence of a short circuit fault, the phase difference feature and the wavelet energy feature in the characteristic component data are reconstructed by complex impedance to obtain impedance spectrum data. The acquisition of impedance spectrum data is based on the equivalent circuit model of the battery. By performing complex operations on the phase difference feature and the wavelet energy feature, the equivalent impedance parameters of the battery are reconstructed, and the internal state of the battery is characterized by this. The complex impedance reconstruction method uses the inverse Fourier transform and polar coordinate transformation methods, that is, the phase difference characteristics are converted into impedance angles, the wavelet energy characteristics are converted into impedance amplitudes, and the impedance spectrum data is obtained through polar coordinate transformation. Since short-circuit faults can cause the equivalent impedance of the battery to mutate within a specific frequency range, the occurrence of short-circuit faults can be confirmed by analyzing the impedance spectrum data. The Euclidean distance of the impedance spectrum data is calculated to measure the deviation between the current impedance spectrum data and the impedance spectrum under normal working conditions, so as to judge the severity of the short-circuit fault and obtain the impedance feature judgment result. Hysteresis judgment is performed based on the voltage feature judgment result, the current feature judgment result, and the impedance feature judgment result to obtain a multi-level fault judgment result.The purpose of hysteresis judgment is to avoid misjudgment caused by short-term noise or transient fluctuations. Therefore, when performing multi-level fault judgment, an appropriate hysteresis threshold is set to ensure the stability of fault judgment.

[0018] Step S5, starting the three-loop nested control structure according to the multi-level fault judgment result, inputting the calculation results of the current tracking control, the power balance control and the state protection control into the PWM modulation unit, and obtaining the control compensation signal; Specifically, the operating state of the current energy storage battery pack is determined according to the multi-level fault judgment results, and the appropriate control strategy is selected according to the severity of the short-circuit fault. If the detection results show that the working state of the battery pack is still within the safe range, the system continues to maintain the current control strategy, and if a short-circuit fault is detected, the control parameters are immediately adjusted to optimize the power flow to reduce the impact of the short-circuit fault. During the startup process of the three-loop nested control structure, the state protection controller of the outer loop performs calculations. The main function of the controller is to build a safe operating boundary based on the key operating parameters of the yacht energy storage battery pack, such as temperature, terminal voltage and current limit. The construction of the safe operating boundary is achieved by setting a threshold range, where the temperature limit is used to prevent the battery pack from accelerating aging or causing thermal runaway due to overheating, the voltage limit is used to avoid performance degradation caused by overcharging or over-discharging of the battery, and the current limit is used to suppress the damage of abnormal short-circuit current to the internal structure of the battery. During the outer loop calculation process, the state protection controller monitors the operating state of the battery pack in real time, and combines the short-circuit detection results to determine whether it is necessary to enter the protection mode. If the calculation results show that the battery has exceeded the safe operating boundary, the state protection controller will generate a state protection instruction to reduce the output power of the battery pack, or trigger the circuit breaker protection mechanism in extreme cases to prevent the fault from further deteriorating. After the state protection instruction is generated, the instruction is passed as an input signal to the power balance controller in the three-ring nested control structure to enter the middle ring calculation stage. The power balance controller dynamically adjusts the power output of the battery pack according to the start-stop transition conditions and the steady-state conditions of the yacht to ensure that the system can still maintain basic energy supply when a short-circuit fault occurs. Since the operating state of the yacht has a large variability, for example, the power demand for the battery is not the same during acceleration, deceleration and steady-state navigation, the power balance controller needs to calculate based on the real-time working conditions and dynamically allocate power output so that the battery pack can stably meet the load demand. In the specific implementation process, the controller adopts model predictive control or adaptive fuzzy control methods to ensure that the power distribution can remain stable in a complex marine environment while minimizing the impact of short-circuit faults on system performance. During the calculation process, the power balance controller will combine the state protection instruction to optimize the output power of the battery and generate a power balance instruction. When the power balance command is generated and enters the inner loop calculation stage of the three-loop nested control structure, the current tracking controller performs the current tracking calculation. The current tracking controller accurately tracks the target current according to the real-time current demand of the battery pack, and adjusts the output state of the battery pack through PWM modulation to ensure the accuracy of current distribution. During the current tracking control calculation process, a dynamic current model of the battery pack is constructed. The model is established through the state space method based on electrochemical impedance, so as to accurately predict the transient response of the current.Based on the model, the current tracking controller uses proportional integral differential control or sliding mode control method to track the target current and calculate the PWM control instruction. The instruction is input to the PWM modulation unit to generate the corresponding PWM duty cycle signal and adjust the power output of the battery in real time to match the optimal power allocation strategy under short-circuit fault conditions. The PWM control instruction is input to the PWM modulation unit system to generate a PWM waveform signal. The PWM waveform signal is digitally filtered to eliminate unnecessary high-frequency components and obtain a smoother control signal. The PWM signal is low-pass filtered using a finite impulse response (FIR) or infinite impulse response (IIR) filter to remove high-frequency noise while retaining the low-frequency effective components. After filtering, a filtered compensation signal is obtained. The filtered compensation signal is multi-loop corrected and calculated with the state protection instruction and the power balance instruction to obtain an optimized control compensation signal. In the multi-loop correction calculation process, the state protection instruction and the power balance instruction are weighted to ensure that the control compensation signal can maintain a reasonable weight distribution under different fault levels. The filtered compensation signal is optimized and adjusted through fuzzy control or Kalman filtering method to adapt to the dynamically changing system requirements and ensure the stability of the output signal.

[0019] Step S6: input the control compensation signal into the current sharing controller, adjust the PWM duty cycle of the parallel branch, and obtain a current sharing control signal.

[0020] Specifically, the control compensation signal is subjected to branch current collection to determine the current distribution of each parallel branch. In a parallel battery system, the current distribution of each branch is not completely uniform, and is limited by factors such as the internal resistance of the battery, the impedance of the connecting cable, and temperature changes. Therefore, the PWM duty cycle is adjusted by real-time monitoring of the current of each branch to maintain the current balance of the entire system. In this process, the current sensor samples the current of each branch with high precision, and uses the digital signal processing unit to calculate the current mean of each branch. At the same time, the branch with the largest current is identified and defined as the main branch to obtain the master-slave branch configuration data. The control compensation signal is subjected to PI parameter calculation according to the master-slave branch configuration data to obtain the optimal PI control parameters. Since the PI controller has good stability and response characteristics in current sharing control, the PI controller is used to adjust the PWM duty cycle to ensure that the current deviation of each branch can be within the allowable range. The calculation of the PI parameters is based on the current difference between the main branch and the slave branch, and is adaptively adjusted in combination with the dynamic response characteristics of the system. In the specific implementation process, the deviation between the main branch current and each slave branch current is calculated, and the proportional gain (Kp) and integral gain (Ki) of the PI control are calculated based on the deviation. Then, the PI parameters are optimized through online adjustment to ensure the rapid convergence and stable operation of the current sharing control. In the process of PI parameter calculation, the load characteristics and temperature influence of the battery are considered to avoid system oscillation or control lag due to improper PI parameters.

[0021] The deviation between the real-time current and the average current of each parallel branch is calculated, and the calculated PI control parameters are input into the current sharing controller to obtain the PWM duty cycle compensation value. The calculation of the PWM duty cycle compensation value is based on the current sharing control target, that is, the currents of all parallel branches should tend to be the same. Therefore, the system calculates the deviation between the real-time current of each branch and the average current of the system, and uses the PI controller to calculate the correction amount of the PWM duty cycle, so that the branch with larger current reduces the output, and the branch with smaller current increases the output, thereby gradually achieving current sharing. In order to further improve the control accuracy, an adaptive weight adjustment mechanism is adopted, that is, when calculating the PWM compensation value, the control weight is dynamically adjusted according to the load condition and operating status of each branch to improve the adaptability of current sharing control. The overcurrent protection judgment of the parallel branch is carried out according to the PWM duty cycle compensation value to prevent a branch from being damaged by overcurrent due to short circuit or other faults. The core principle of overcurrent protection judgment is to compare the real-time current of each branch with the set safety threshold. If the current of a branch exceeds the safety threshold, the system immediately triggers the overcurrent protection instruction to limit the output of the branch or directly cut off the circuit to prevent damage to the battery or related electronic equipment. The overcurrent protection instruction is input into the power regulation unit to adjust the output power of the yacht energy storage battery and generate a power regulation signal. If the system detects an overcurrent in a branch, it is necessary to dynamically adjust the power output of the entire system to avoid the impact of power imbalance on the energy supply of the yacht. The power regulation signal is subjected to current sharing compensation calculation to obtain a current sharing control signal. The current sharing compensation calculation adopts a dynamic adaptive algorithm, that is, under different load conditions, the gain coefficient of the current sharing control is automatically adjusted to ensure the stability and rapid response capability of the control.

[0022] In the embodiment of the present invention, by adopting a three-level RC parallel network model and combining with the correction of marine environmental parameters, the dynamic characteristics of yacht energy storage batteries under different working conditions are accurately described; by the combined application of sliding window Fourier transform and wavelet packet decomposition, multi-scale feature extraction is realized, and the integrity of feature information is enhanced; a three-level judgment mechanism based on voltage mutation, current mutation and impedance spectrum is designed, and hysteresis comparison processing is introduced to improve the reliability of fault detection; a three-loop nested control structure is proposed to realize the coordinated control of state protection, power balance and current tracking, and ensure the stability of system output; based on the master-slave current sharing control strategy, the current distribution problem of parallel branches is effectively solved, and the dynamic response capability of the system is improved. The present invention enhances the safety and reliability of the system through the coordinated cooperation of multi-level protection and control strategies.

[0023] In a specific embodiment, the process of executing step S1 may specifically include the following steps: Perform differential amplification on the sampling channel of the voltage acquisition unit to obtain a voltage acquisition gain coefficient, and input the voltage acquisition gain coefficient into the voltage sampling circuit to perform 16-bit precision sampling on multiple series-connected battery cells of the yacht energy storage battery pack to obtain voltage sampling data; Performing operational amplification on the output signal of the Hall sensor of the current acquisition unit to obtain a current acquisition gain coefficient, and inputting the current acquisition gain coefficient into the current sampling circuit, performing 16-bit precision sampling on the two parallel branches to obtain current sampling data; The voltage sampling data and the current sampling data are converted into 12-bit ADC to obtain digital sampling data, and the digital sampling data is transmitted to the digital signal processor through the CAN bus, and the received data is verified to obtain the original sampling data.

[0024] Specifically, the sampling channel of the voltage acquisition unit is differentially amplified to reduce the influence of common mode noise and improve the signal quality of the measurement. In the voltage sampling process, since the yacht energy storage battery pack is composed of multiple series-connected single cells, a differential amplifier circuit is constructed through a high-precision operational amplifier so that the sampling signal can accurately reflect the terminal voltage of each battery cell. Assume that the terminal voltage of a battery cell is , then the signal amplified by the differential amplifier circuit is expressed as:

[0025] in, is the voltage acquisition gain coefficient, and They are the voltages at the positive and negative ends of the battery cell, respectively. By accurately measuring the gain coefficient, it is ensured that the subsequent sampling circuit can correctly convert the voltage signal and input it into the voltage sampling circuit for high-precision sampling. In the voltage sampling circuit, in order to ensure the measurement accuracy, a 16-bit ADC (analog-to-digital converter) is used to sample multiple series-connected battery cells of the yacht energy storage battery pack. During the sampling process, the measured values ​​of each battery cell are stored in the data register in turn, and uniformly sampled through a time synchronization mechanism to avoid misjudgment of the battery status due to sampling time offset. At the same time, in the current acquisition unit, since the output signal of the Hall sensor is usually weak and easily disturbed by the external magnetic field, the output signal of the Hall sensor is operationally amplified to enhance the signal amplitude and improve the signal-to-noise ratio. The current signal output by the Hall sensor changes in the milliampere level, and the sampling circuit requires a higher signal level to ensure the measurement accuracy. An operational amplifier is used to construct a gain circuit so that the amplified signal reaches the optimal input range of the ADC. Assume that the Hall sensor outputs a current signal Current-to-voltage conversion resistor Converted into voltage signal , then its expression is written as:

[0026] After amplification by the operational amplifier, the voltage signal obtained is:

[0027] in, It is the current acquisition gain factor, which determines the amplitude of the amplified signal. By accurately measuring the gain factor and inputting it into the current sampling circuit, the current of the two parallel branches can be measured with high precision. During the current sampling process, a 16-bit ADC is used for sampling to ensure the accuracy of the sampled data. The sampled data is converted to 12-bit ADC to reduce the burden of data storage and transmission. The 12-bit ADC conversion process is implemented through a data reduction algorithm, such as using a mean filter, that is, weighted averaging of the 16-bit sampled data to reduce noise and improve the smoothness of the data. For example, if the 16-bit data Need to convert to 12-bit data , then the conversion formula is written as:

[0028] This conversion process effectively reduces data redundancy while retaining the main signal characteristics, making it suitable for subsequent data transmission and processing. After the data conversion is completed, in order to ensure that the sampled data is reliably transmitted to the digital signal processor (DSP), communication is carried out through the CAN (Controller Area Network) bus. The CAN bus is an efficient and anti-interference data transmission protocol suitable for the complex electromagnetic environment of yacht energy storage systems. During the data transmission process, the digital sampled data is packaged according to a predetermined data format. For example, each data frame contains voltage data, current data and timestamp information, and then encoded through the CAN protocol and sent to the DSP. The DSP receives the data and performs data verification to ensure the integrity and correctness of the transmission. The data verification methods include CRC (cyclic redundancy check) and parity check, where the calculation formula for CRC verification is:

[0029] in, Represents each byte of the data frame, It is a preset polynomial check code. If the calculated CRC value matches the CRC value calculated by the receiving end, it means that the data transmission is normal, otherwise a retransmission is required to ensure the integrity of the data. After completing the data check, the original sampled data is stored in the DSP buffer area and used for subsequent short circuit detection and energy management calculations.

[0030] In a specific embodiment, the process of executing step S2 may specifically include the following steps: The original sampling data is corrected for ocean environmental parameters according to the temperature coefficient and humidity coefficient to obtain environmental correction data; The environmental correction data is input into the three-level RC parallel network model, the fast charge and discharge response branch time constant is set to the first target value, the start-stop transition branch time constant is set to the second target value, and the navigation steady-state branch time constant is set to the third target value, and the yacht operating condition RC branch parameters are obtained; The RC branch parameters of yacht working condition are discretized, and the capacitor voltage and temperature state of the three-level RC parallel network model are taken as state variables to obtain the extended discrete state equation. The response data of the battery pack under different temperature, humidity and load conditions are calculated by the least square method according to the extended discrete state equation to obtain the environmental adaptive parameter matrix; Perform multivariate correlation calculation on the environmental adaptive parameter matrix, establish the mapping relationship between RC parameters and temperature, humidity and charge state, and obtain the RC parameter correction value; The RC parameter correction values ​​are updated to the extended discrete state equation for numerical calculation to obtain the RC network dynamic response data.

[0031] Specifically, the original sampling data is corrected based on the temperature coefficient and humidity coefficient to obtain environmental correction data that is more in line with the actual operating status. The original sampling data includes voltage and current And the environmental variable temperature and humidity , where temperature and humidity will affect the equivalent internal resistance, polarization voltage and charge and discharge efficiency of the battery. Use the empirical model to compensate for these effects, namely:

[0032]

[0033] in, and are the voltage and current corrected for temperature and humidity, respectively. and is the reference temperature and humidity, and is the temperature correction factor, and is the humidity correction factor. Through correction, the influence of environmental changes on battery performance is effectively compensated. The environmental correction data is input into the three-level RC parallel network model to construct an equivalent circuit model that can accurately describe the yacht working conditions. The three-level RC network model consists of three parallel RC branches, each of which represents the dynamic characteristics of the battery under different time scales. The fast charge and discharge response branch mainly describes the double-layer capacitance effect of the battery, and its time constant is is set as the first target value to capture the voltage change of the battery in a short time, expressed as:

[0034] in, is the equivalent resistance of the fast response branch, It is the equivalent capacitance of the fast charge and discharge branch. The start-stop transition branch is used to describe the electrochemical polarization of the battery during the start-stop process. Its time constant is Set as the second target value, determined by the characteristics of the SEI film:

[0035] in, and are the equivalent resistance and capacitance of the start-stop branch respectively. The navigation steady-state branch is used to describe the slow release of energy from the battery during long-term navigation. Its time constant Set as the third target value to ensure the accuracy of long-term steady-state calculations:

[0036] in, and Represents the equivalent resistance and capacitance of the steady-state branch. Through the above settings, it is ensured that the three-level RC network model can accurately simulate the charging and discharging behavior of the battery at different time scales. When establishing the RC model, the RC branch parameters of the yacht working condition are discretized for computer implementation. Since the differential equation of the RC circuit is continuous, the numerical discretization method is used to convert it into a state equation suitable for numerical calculation. In the discretization process, the state variables are defined, including the capacitor voltage of each branch And temperature status , then the continuous state equation is expressed as:

[0037]

[0038]

[0039]

[0040] in, is the temperature increment coefficient determined by the Joule heating effect, is the thermal conductivity, is the ambient temperature. Through discretization, the above equation is converted into a discrete state equation:

[0041]

[0042]

[0043]

[0044] The extended discrete state equation is obtained, which is used for battery modeling calculation under different temperature, humidity and load conditions. In order to further optimize the RC parameters, the battery response data under different environmental conditions are fitted based on the least squares method to obtain the environmental adaptive parameter matrix. Set the error function:

[0045] in, is the measured voltage, is the voltage calculated by the model. By solving the least squares solution:

[0046] in, is the feature matrix, is the measurement data, is the parameter to be estimated, and the environmental adaptive parameter matrix is ​​obtained. Multivariate correlation calculation is performed on the matrix to establish the relationship between RC parameters and temperature, humidity and charge state. The mapping relationship is:

[0047] ; The corrected Substituting the extended discrete state equation and performing numerical calculations, the final RC network dynamic response data is obtained to realize battery modeling based on marine environment correction.

[0048] In a specific embodiment, the process of executing step S3 may specifically include the following steps: Perform sliding window processing on the RC network dynamic response data and the original sampling data to obtain the spectrum leakage-free data; The de-spectral leakage data is input into a second-order Butterworth low-pass filter to obtain pre-processed signal data; Perform fast Fourier transform operation on the preprocessed signal data to obtain frequency domain feature data; Calculate the phase difference between adjacent characteristic frequency points according to the frequency domain characteristic data to obtain phase difference characteristic data; Perform wavelet packet decomposition on the preprocessed signal data to obtain wavelet energy characteristic data; The frequency domain feature data, phase difference feature data and wavelet energy feature data are vector mapped and fused to obtain the target feature vector.

[0049] Specifically, RC network dynamic response data and the original sample data As input signals, they are non-stationary, that is, their spectral characteristics change over time. Sliding window processing is used, that is, signal data is intercepted within a fixed time window, and frequency domain analysis is performed on each window separately. Assume that the sliding window length is , then for any time , the signal in the sliding window is expressed as:

[0050] in, Represents the instantaneous value of the RC network dynamic response data or the original sampled data. The sliding window slides continuously on the time series data with a fixed step size. Update so that subsequent calculations can cover the entire signal. After completing the sliding window processing, the data is processed to remove spectrum leakage. Spectral leakage is the phenomenon of spectrum energy expansion caused by signal truncation and window mismatch during FFT calculation. In order to suppress this problem, the data in the sliding window is multiplied by the window function , the window function includes Hanning window, Ham window, etc. The signal after windowing is expressed as:

[0051] in, Select the Hanning window:

[0052] Effectively reduce the spectrum leakage during FFT calculation and obtain the spectrum leakage-free data. Input the spectrum leakage-free data into the second-order Butterworth low-pass filter to remove high-frequency noise and smooth the signal. The characteristic of the Butterworth filter is that the amplitude-frequency response curve is flat, so that the signal remains intact in the low-frequency part, while the high-frequency part is effectively attenuated. Its transfer function is:

[0053] in, is the cut-off angular frequency, is the Laplace transform variable. By discretizing the input signal, the difference equation of the second-order Butterworth filter is written as:

[0054] in, is the filtered signal, is the input signal, the coefficient It is determined by the filter design. The signal after filtering is the pre-processed signal data. In order to analyze the frequency domain characteristics of the signal, the pre-processed signal data is subjected to fast Fourier transform (FFT), and its mathematical expression is:

[0055] in, is the frequency domain signal, is the time domain signal, is the number of FFT points, is the frequency. The calculation result of FFT can intuitively reflect the spectrum characteristics of the signal and is used for subsequent feature analysis. Based on the frequency domain feature data calculated by FFT, the phase difference between adjacent feature frequency points is calculated to extract the phase feature. The formula for phase difference calculation is:

[0056] in, Indicates the phase of the spectrum at a certain frequency point. For the frequency points. The phase difference characteristic data can reflect the phase shift caused by internal short circuit or nonlinear impedance change of the battery. Wavelet packet decomposition is performed on the preprocessed signal data. Wavelet packet decomposition is a time-frequency analysis method that decomposes the signal into components of different frequency bands to obtain more detailed spectrum information. Set the mother wavelet function to , then the wavelet packet transform of the signal is expressed as:

[0057] in, Indicates the decomposition level, Represents the frequency band index. The energy feature calculation formula obtained by wavelet packet decomposition is:

[0058] This energy feature can effectively characterize the energy distribution of the signal in different frequency bands, and thus be used for fault feature extraction. Vector mapping is performed on the frequency domain feature data, phase difference feature data, and wavelet energy feature data to normalize and standardize different types of features. The normalization process uses minimum-maximum normalization:

[0059] in, and are the minimum and maximum values ​​of the feature data respectively. The standardization process uses zero mean normalization:

[0060] in, is the feature mean, is the characteristic standard deviation. The characteristic data after normalization and standardization are fused into characteristic vectors to form the final target characteristic vector. The fusion method uses principal component analysis:

[0061] in, is the dimension reduction matrix, is the feature vector. The target feature vector finally generated is used for short circuit detection and subsequent battery management optimization.

[0062] In a specific embodiment, the process of executing step S4 may specifically include the following steps: Performing vector demapping processing on the target feature vector to obtain feature component data; The voltage drop amplitude is calculated for the frequency domain characteristics in the characteristic component data to obtain the voltage characteristic judgment result; According to the voltage characteristic judgment result, the current slope is calculated for the frequency domain characteristics in the characteristic component data to obtain the current characteristic judgment result; The phase difference feature and wavelet energy feature in the characteristic component data are reconstructed by complex impedance to obtain impedance spectrum data; The Euclidean distance calculation is performed on the impedance spectrum data to obtain the impedance feature judgment result; A hysteresis judgment is performed based on the voltage characteristic judgment result, the current characteristic judgment result and the impedance characteristic judgment result to obtain a multi-level fault judgment result.

[0063] Specifically, the target feature vector is subjected to vector demapping to extract independent feature component data. The target feature vector is formed by fusion of different types of signal features, including frequency domain features, voltage mutation features, current mutation features, phase difference features, and wavelet energy features. In the demapping process, the fused feature vector is mapped according to the feature category. Mapping back to its original feature space, assuming the target feature vector is:

[0064] in, represents the frequency domain characteristics, represents the phase difference characteristic, Represents the wavelet energy feature. The demapping process is performed through the inverse principal component analysis or independent component analysis method to restore the feature vector to independent feature component data for subsequent calculations. The voltage drop is calculated to determine whether the voltage characteristics are abnormal. A short circuit fault is accompanied by a sudden drop in voltage, so the transient drop in voltage is calculated to determine whether a short circuit occurs. The voltage drop calculation is expressed as:

[0065] in, is the voltage drop, is the reference voltage under normal working conditions, is the current measured voltage. If Exceeding the set threshold , it is determined that the battery may have a short circuit tendency:

[0066] The calculation result of this step is the voltage characteristic judgment result. Based on the voltage characteristic judgment result, the current slope is calculated for the frequency domain characteristics to determine the current mutation. When short-circuited, the current will rise sharply, so the current slope is calculated to determine whether there is an abnormality. Assume that the current sampling data is , then the current slope calculation formula is:

[0067] in, represents the rate of change of current, is the current at the current moment, is the current at the previous moment, is the sampling time interval. If the current slope exceeds the set mutation threshold , then it is determined that the current is abnormal:

[0068] This result is the current characteristic judgment result. In order to analyze the internal impedance change of the battery, the phase difference feature in the characteristic component data is used and wavelet energy characteristics Perform complex impedance reconstruction. The complex impedance is expressed as:

[0069] in, is the equivalent resistance component of the battery, is the equivalent reactance component of the battery. The key to impedance reconstruction is to use the phase difference feature Calculate the impedance angle:

[0070] At the same time, wavelet energy characteristics It reflects the energy changes in different frequency bands and is used to calculate the impedance amplitude:

[0071] This solves for the real and imaginary parts of the impedance:

[0072] Finally, the impedance spectrum data is obtained. In order to quantify the deviation between the impedance spectrum data and the normal working state, the Euclidean distance calculation is performed on the impedance spectrum data to obtain the impedance feature judgment result. Assuming that the impedance data under normal working conditions is , then the Euclidean distance between the current impedance and the normal impedance is:

[0073] if Exceeding the set threshold , then the impedance is judged to be abnormal:

[0074] This result is the impedance feature judgment result. Hysteresis judgment is performed based on the voltage feature judgment result, current feature judgment result and impedance feature judgment result to obtain the final multi-level fault judgment result. The purpose of hysteresis judgment is to avoid misjudgment caused by short-term noise or transient changes. In the final judgment process, a hysteresis interval is set. Assume that the fault judgment variable The combination of the three is defined as:

[0075] in, is the weight factor, Represent the fault judgment results of voltage, current and impedance respectively. Then set the hysteresis threshold:

[0076] when When , the fault is judged as a short circuit; when When , the system is judged to be normal; when , the state of the previous moment is maintained to prevent misjudgment: ; This judgment strategy can effectively reduce misjudgment and improve the reliability of fault detection.

[0077] In this embodiment, a three-loop nested control structure is started according to the multi-stage short-circuit fault judgment result, and the calculation results of the current tracking control, the power balance control and the state protection control are input into the PWM modulation unit to obtain the control compensation signal. The following also includes: offline training processing of historical operating condition data, inputting the voltage, current and power data of the yacht energy storage battery pack under different navigation conditions into the recursive balancing network to obtain network training parameters; constructing a neural network prediction model according to the network training parameters, taking the multi-stage short-circuit fault judgment result as the input variable to obtain fault operating condition prediction data; performing fast response strategy calculation on the fault operating condition prediction data, setting the control period to 10μs, setting the calculation accuracy to 16 bits, and obtaining control strategy parameters; inputting the control strategy parameters into the digital signal processing The processor is used to optimize the control gain of the three-loop nested control structure online to obtain the optimal control parameters; the bandwidth of the current tracking control loop is dynamically adjusted based on the optimal control parameters, and the bandwidth range is set between 500Hz and 2kHz to obtain the bandwidth adjustment coefficient; the response speed of the power balance control loop is corrected according to the bandwidth adjustment coefficient, and the response time is controlled within 2ms to obtain the response speed compensation value; the stability of the response speed compensation value and the state feedback signal of the three-loop control structure is analyzed, and the Lyapunov function is constructed for closed-loop stability judgment to obtain the stability criterion; the control parameters of the three-loop nested control structure are asymptotically converged according to the stability criterion to obtain the converged control parameters, and the converged control parameters are updated to the three-loop nested control structure.

[0078] In a specific embodiment, the process of executing step S5 may specifically include the following steps: The three-loop nested control structure is started according to the multi-level fault judgment result, and the outer loop calculation is performed through the state protection controller in the three-loop nested control structure. The safe operation boundary is built according to the temperature limit, voltage limit and current limit of the yacht energy storage battery pack to obtain the state protection instruction; According to the state protection instruction, the power balance controller in the three-loop nested control structure performs mid-loop calculation, and dynamically allocates the power demand under the yacht start-stop transition condition and the navigation steady-state condition to obtain the power balance instruction; According to the power balance instruction, the current tracking inner loop calculation is performed on the current tracking controller in the three-loop nested control structure to obtain the PWM control instruction, and the PWM control instruction is input into the PWM modulation unit to adjust the duty cycle in real time to obtain the PWM waveform signal; The PWM waveform signal is digitally filtered to obtain a filter compensation signal, and the filter compensation signal is subjected to multi-loop correction calculation with a state protection instruction and a power balance instruction to obtain a control compensation signal.

[0079] Specifically, the three-loop nested control structure is activated according to the multi-level fault judgment results, and the state protection controller performs the outer loop calculation to ensure the operation safety of the yacht energy storage battery pack. The core of the state protection controller is based on the temperature limit of the battery pack. , Voltage Limit , Current Limit Construct a safe operation boundary to ensure that the system operates within a reasonable working range. In order to construct this boundary, define a safety judgment function:

[0080] in, Indicates whether the system is in a safe area. When the system can operate normally; when When the state protection controller generates a state protection instruction, it means that a certain parameter exceeds the allowable range and the system operation state needs to be adjusted. :

[0081] in, are the weighting factors for temperature, voltage, and current, respectively, used to adjust the sensitivity of the protection strategy. , it means that the system needs to take protective measures, such as reducing the charging power or reducing the discharge current. The state protection instruction is input into the power balance controller of the three-ring nested control structure, and the middle-loop calculation is performed. The power balance controller dynamically allocates the power output of the energy storage battery pack based on the different operating conditions of the yacht, such as start-stop transition conditions and steady-state navigation conditions. Under the start-stop transition conditions, the yacht's power demand will fluctuate greatly, so the power balance controller responds quickly to maintain the stability of the system. Under steady-state navigation conditions, the system optimizes power output to extend battery life and improve energy efficiency. The power demand is expressed as:

[0082] in, is the current total power demand of the yacht, The power requirement for the propulsion system is The power balance controller is based on the state protection instructions. Adjust the power allocation strategy:

[0083] in, is the power value finally allocated to the battery system. In order to ensure the smoothness of power distribution, a PI controller is used to adjust the power error:

[0084] in, and are the proportional and integral gain parameters, It is a power balance control instruction. This instruction is used to optimize the battery output to adapt it to the current load demand. Entering the inner loop calculation stage of the three-loop nested control structure, the current tracking controller performs current tracking calculations and generates PWM control instructions. The goal of current tracking control is to ensure that the current output of the energy storage battery pack matches the system requirements to maintain a stable voltage output. Assume that the target current is , then the current tracking error is:

[0085] in, is the actual measured current value. Use sliding mode control or PI control to calculate the PWM duty cycle:

[0086] in, is the initial duty cycle, is the adjusted PWM duty cycle. The calculated PWM control command is input into the PWM modulation unit to adjust the duty cycle in real time and generate a PWM waveform signal to control the energy output of the battery. In order to improve the stability of the PWM signal, the PWM waveform signal is digitally filtered to reduce the influence of high-frequency harmonics. The filtering process uses a finite impulse response (FIR) filter or a Butterworth filter, and its transfer function is:

[0087] in, is the cut-off angular frequency, is the Laplace transform variable. The filtered signal is the filter compensation signal , and its calculation formula is:

[0088] in, is the weight coefficient of the filter, is the filter order. After filtering, the PWM signal is smoother, which helps to reduce current ripple and improve system stability. The filter compensation signal is multi-loop corrected with the state protection instruction and the power balance instruction to obtain the final control compensation signal. The three control signals are combined using a weighted fusion method:

[0089] in, is the weighting coefficient, which is used to adjust the contribution of different signals. The signal is sent to the battery management system (BMS) to adjust the battery output in real time to adapt it to the current operating conditions and ensure the safety and stability of the system operation.

[0090] Optionally, the power balance controller in the three-ring nested control structure is calculated in the middle loop according to the state protection instruction, and the power demand under the yacht start-stop transition condition and the steady-state navigation condition is dynamically allocated to obtain the power balance instruction, including: constructing multiple parallel branches of the yacht energy storage battery pack into a unified energy boundary model, coupling the total power and energy capacity between the branches to obtain energy storage boundary parameters; constructing a multivariate regression prediction model according to the energy storage boundary parameters and historical navigation data, and performing probability distribution calculation on the power demand of the future voyage to obtain power prediction data; performing risk value assessment on the power prediction data, dividing the navigation condition into a high-speed navigation section, a low-speed cruising section and a port mooring section to obtain the segmented power demand. rate threshold; based on the segmented power threshold, the energy storage system is optimally allocated power, a two-stage stochastic optimization model is constructed, and a power allocation strategy is obtained; the power allocation strategy is input into the adaptive predictive controller, and the allocation strategy is corrected online according to the real-time navigation status to obtain a corrected control instruction; the energy storage capacity is dynamically allocated according to the corrected control instruction, and the standby power during navigation is adjusted in real time to obtain a dynamic power compensation value; a power balance calculation is performed on the dynamic power compensation value, and the output power of each parallel branch is limited within a set range to obtain a power limit instruction; the power limit instruction is coordinated with the state protection instruction, and the output power of the energy storage system is uniformly regulated to obtain a power balance instruction.

[0091] In a specific embodiment, the process of executing step S6 may specifically include the following steps: The control compensation signal is subjected to branch current collection, the branch with the largest current is set as the main branch, and the main-slave branch configuration data is obtained; Calculate the PI parameters of the control compensation signal according to the master-slave branch configuration data to obtain the PI control parameters; The deviation between the real-time current and the average current of each parallel branch is calculated, and the PI control parameter is input into the current sharing controller to obtain the PWM duty cycle compensation value; Perform over-current protection judgment on the parallel branch according to the PWM duty ratio compensation value to obtain an over-current protection instruction; The overcurrent protection instruction is input into the power regulation unit to adjust the output power of the yacht energy storage battery to obtain a power regulation signal, and a current sharing compensation calculation is performed on the power regulation signal to obtain a current sharing control signal.

[0092] Specifically, the instantaneous current of each parallel branch is High-precision sampling is performed to ensure that the system can correctly identify the branch with the largest current and set it as the main branch. Assume that the yacht energy storage battery pack has There are parallel branches, and the current collection values ​​of each branch are , then the current in the main branch is defined as:

[0093] At this time, the branch with the largest current is the main branch, and its index Determined by the following formula:

[0094] The other branches are set as slave branches, and the configuration data of the master and slave branches are recorded and used for subsequent current sharing control calculations. The PI parameter calculation of the control compensation signal is performed based on the master and slave branch configuration data to obtain the optimized PI control parameters. The core task of the PI controller is to adjust the current of each branch so that it tends to be balanced, so the objective function of the PI control is defined as:

[0095] in, is the average current of all branches, and the calculation formula is as follows:

[0096] error Represents the current deviation of a branch. When the value is not zero, it means that the current distribution is unbalanced, which can be corrected by adjusting the PWM duty cycle. The control law of the PI controller is:

[0097] in, is the compensation value of the PWM duty cycle of this branch, is the proportional gain, is the integral gain. This formula ensures that the branch with large current deviation can adjust its output through PWM to approach the current sharing state. After calculating the PI control parameters, the deviation between the real-time current and the average current of each parallel branch is calculated, and the PWM duty cycle compensation value is calculated using the PI control parameters to input the current sharing controller for the final current sharing adjustment. The input signal of the current sharing controller includes the current error at the current moment and the compensation signal calculated by the PI controller , whose output is the corrected PWM duty cycle:

[0098] in, is the initial PWM duty cycle, and the adjusted Input to the PWM modulation unit to correct the power output of each branch. After obtaining the PWM duty cycle compensation value, determine whether there is an overcurrent risk in each branch to ensure the safe operation of the system. The core idea of ​​overcurrent protection judgment is to calculate the current of each branch. With the set overcurrent threshold If the current of a branch exceeds the threshold, the system should trigger the overcurrent protection instruction. :

[0099] like , indicating that the branch has entered an overcurrent state. At this time, reduce its PWM duty cycle to reduce current output and avoid damaging the battery or other components. The specific adjustment strategy is as follows:

[0100] in, The value of the adjustment coefficient determines the response speed of the overcurrent protection. The overcurrent protection command is input into the power regulation unit to adjust the overall power output of the yacht energy storage battery and generate a power regulation signal. The basic principle of power regulation is to ensure the total power Meet load requirements while maintaining current sharing:

[0101] Among them, the power output of each branch is:

[0102] If some branches reduce power output due to overcurrent protection, the power of other branches is dynamically adjusted so that the total power can still meet the load requirements. The regulation strategy adopts the proportional allocation method, that is:

[0103] in, is the total power reduced by overcurrent protection, the remaining The power is distributed proportionally to the branches to maintain power stability. The power regulation signal is subjected to current sharing compensation calculation to finally generate a current sharing control signal. The key to current sharing compensation is to ensure that the power output of each branch is relatively balanced, so the corrected current sharing error is calculated:

[0104] If the value exceeds the set threshold, the parameters of the current sharing controller are adjusted to optimize the PWM duty cycle distribution:

[0105] in, is the current sharing compensation coefficient, which is used to accelerate the convergence speed of current sharing control.

[0106] The above describes the internal short circuit detection method of the yacht energy storage battery in the embodiment of the present invention. The following describes the internal short circuit detection device of the yacht energy storage battery in the embodiment of the present invention. Figure 2 In one embodiment of the present invention, a device for detecting internal short circuit of a yacht energy storage battery comprises: The sampling module is used to sample the voltage and current of the yacht energy storage battery pack to obtain the original sampling data; The parameter identification module is used to input the original sampling data into the three-level RC parallel network model for parameter identification to obtain the RC network dynamic response data; A decomposition module is used to perform sliding window Fourier transform and wavelet packet decomposition on the RC network dynamic response data and the original sampling data to obtain the target feature vector; A judgment module is used to judge voltage mutation characteristics, current mutation characteristics and impedance spectrum characteristics based on the target feature vector to obtain multi-level fault judgment results; A control compensation module is used to start a three-loop nested control structure according to the multi-level fault judgment results, input the calculation results of current tracking control, power balance control and state protection control into the PWM modulation unit, and obtain a control compensation signal; The current sharing control module is used to input the control compensation signal into the current sharing controller, adjust the PWM duty cycle of the parallel branch, and obtain the current sharing control signal.

[0107] Through the synergy of the above-mentioned components, by adopting a three-level RC parallel network model and combining with the correction of marine environmental parameters, the dynamic characteristics of yacht energy storage batteries under different working conditions are accurately described; through the combined application of sliding window Fourier transform and wavelet packet decomposition, multi-scale feature extraction is realized, and the integrity of feature information is enhanced; a three-level judgment mechanism based on voltage mutation, current mutation and impedance spectrum is designed, and hysteresis comparison processing is introduced to improve the reliability of fault detection; a three-loop nested control structure is proposed to realize the coordinated control of state protection, power balance and current tracking, and ensure the stability of system output; based on the master-slave current sharing control strategy, the current distribution problem of parallel branches is effectively solved, and the dynamic response capability of the system is improved. The present invention enhances the safety and reliability of the system through the coordinated cooperation of multi-level protection and control strategies.

[0108] Reference Figure 3 In an embodiment of the present invention, a computer device is also provided. The computer device may be a server, and its internal structure may be as follows: Figure 3As shown. The computer device includes a processor, a memory, a display screen, an input device, a network interface and a database connected through a system bus. Among them, the processor designed by the computer is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store the corresponding data in this embodiment. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the above method is implemented.

[0109] Those skilled in the art will understand that Figure 3 The structure shown in the figure is merely a block diagram of a portion of the structure related to the solution of the present invention, and does not constitute a limitation on the computer device to which the solution of the present invention is applied.

[0110] An embodiment of the present invention further provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the above method is implemented. It can be understood that the computer-readable storage medium in this embodiment can be a volatile readable storage medium or a non-volatile readable storage medium.

[0111] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media provided by the present invention and used in the embodiments may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double-speed data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM.

[0112] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described systems, systems and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0113] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or the whole or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk and other media that can store program code.

[0114] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for detecting internal short circuit of a yacht energy storage battery, characterized in that: The method comprises: Sample the voltage and current of the yacht energy storage battery pack to obtain original sampling data; Inputting the original sampling data into a three-level RC parallel network model for parameter identification to obtain RC network dynamic response data; Performing sliding window Fourier transform and wavelet packet decomposition on the RC network dynamic response data and the original sampling data to obtain a target feature vector; Based on the target feature vector, voltage mutation feature judgment, current mutation feature judgment and impedance spectrum feature judgment are performed to obtain a multi-level fault judgment result; A three-loop nested control structure is started according to the multi-level fault judgment result, and the calculation results of the current tracking control, the power balance control and the state protection control are input into the PWM modulation unit to obtain a control compensation signal; The control compensation signal is input into the current sharing controller to adjust the PWM duty cycle of the parallel branch to obtain a current sharing control signal.

2. The method for detecting internal short circuit of a yacht energy storage battery according to claim 1, characterized in that: The voltage and current of the yacht energy storage battery pack are sampled to obtain the original sampling data, including: Perform differential amplification on the sampling channel of the voltage acquisition unit to obtain a voltage acquisition gain coefficient, and input the voltage acquisition gain coefficient into the voltage sampling circuit to perform 16-bit precision sampling on multiple series-connected battery cells of the yacht energy storage battery pack to obtain voltage sampling data; Performing operational amplification on the output signal of the Hall sensor of the current acquisition unit to obtain a current acquisition gain coefficient, and inputting the current acquisition gain coefficient into the current sampling circuit, performing 16-bit precision sampling on the two parallel branches to obtain current sampling data; The voltage sampling data and the current sampling data are converted by 12-bit ADC to obtain digital sampling data, and the digital sampling data is transmitted to a digital signal processor through a CAN bus, and the received data is verified to obtain original sampling data.

3. The method for detecting internal short circuit of a yacht energy storage battery according to claim 1, characterized in that: The raw sampling data is input into a three-level RC parallel network model for parameter identification to obtain RC network dynamic response data, including: Performing ocean environment parameter correction on the original sampling data according to the temperature coefficient and the humidity coefficient to obtain environment correction data; The environmental correction data is input into the three-level RC parallel network model, the fast charge and discharge response branch time constant is set to the first target value, the start-stop transition branch time constant is set to the second target value, and the navigation steady-state branch time constant is set to the third target value, to obtain the yacht operating condition RC branch parameters; The RC branch parameters of the yacht working condition are discretized, and the capacitor voltage and temperature state of the three-level RC parallel network model are used as state variables to obtain an extended discrete state equation; Performing least squares calculation on the response data of the battery pack under different temperature, humidity and load conditions according to the extended discrete state equation to obtain an environmental adaptive parameter matrix; Performing multivariable correlation calculation on the environmental adaptive parameter matrix, establishing a mapping relationship between RC parameters and temperature, humidity and charge state, and obtaining RC parameter correction values; The RC parameter correction value is updated to the extended discrete state equation for numerical calculation to obtain RC network dynamic response data.

4. The method for detecting internal short circuit of a yacht energy storage battery according to claim 1, characterized in that: The step of performing sliding window Fourier transform and wavelet packet decomposition on the RC network dynamic response data and the original sampling data to obtain a target feature vector includes: Performing sliding window processing on the RC network dynamic response data and the original sampling data to obtain spectrum leakage-free data; Inputting the de-spectral leakage data into a second-order Butterworth low-pass filter to obtain pre-processed signal data; Performing a fast Fourier transform operation on the preprocessed signal data to obtain frequency domain feature data; Calculate the phase difference between adjacent characteristic frequency points according to the frequency domain characteristic data to obtain phase difference characteristic data; Performing wavelet packet decomposition on the preprocessed signal data to obtain wavelet energy characteristic data; Vector mapping and vector fusion are performed on the frequency domain feature data, the phase difference feature data and the wavelet energy feature data to obtain a target feature vector.

5. The method for detecting internal short circuit of a yacht energy storage battery according to claim 1, characterized in that: The voltage mutation feature judgment, current mutation feature judgment and impedance spectrum feature judgment are performed based on the target feature vector to obtain a multi-level fault judgment result, including: Performing vector demapping processing on the target feature vector to obtain feature component data; Calculating the voltage drop amplitude on the frequency domain characteristics in the characteristic component data to obtain a voltage characteristic judgment result; According to the voltage characteristic judgment result, current slope calculation is performed on the frequency domain characteristics in the characteristic component data to obtain a current characteristic judgment result; Performing complex impedance reconstruction on the phase difference feature and the wavelet energy feature in the characteristic component data to obtain impedance spectrum data; Performing Euclidean distance calculation on the impedance spectrum data to obtain an impedance feature judgment result; A hysteresis judgment is performed based on the voltage characteristic judgment result, the current characteristic judgment result and the impedance characteristic judgment result to obtain a multi-level fault judgment result.

6. The method for detecting internal short circuit of a yacht energy storage battery according to claim 1, characterized in that: The three-loop nested control structure is started according to the multi-level fault judgment result, and the calculation results of the current tracking control, the power balance control and the state protection control are input into the PWM modulation unit to obtain the control compensation signal, including: The three-loop nested control structure is started according to the multi-level fault judgment result, and the outer loop calculation is performed through the state protection controller in the three-loop nested control structure, and a safe operation boundary is established according to the temperature limit, voltage limit and current limit of the yacht energy storage battery pack to obtain a state protection instruction; According to the state protection instruction, a power balance controller in the three-loop nested control structure is subjected to a mid-loop calculation, and the power demand under the yacht start-stop transition condition and the navigation steady-state condition is dynamically allocated to obtain a power balance instruction; According to the power balance instruction, a current tracking inner loop calculation is performed on the current tracking controller in the three-loop nested control structure to obtain a PWM control instruction, and the PWM control instruction is input into a PWM modulation unit to adjust the duty cycle in real time to obtain a PWM waveform signal; The PWM waveform signal is digitally filtered to obtain a filter compensation signal, and the filter compensation signal is subjected to multi-loop correction calculation with the state protection instruction and the power balance instruction to obtain a control compensation signal.

7. The method for detecting internal short circuit of a yacht energy storage battery according to claim 1, characterized in that: The step of inputting the control compensation signal into the current sharing controller to adjust the PWM duty cycle of the parallel branch to obtain the current sharing control signal includes: The control compensation signal is subjected to branch current collection, the branch with the largest current is set as the main branch, and main-slave branch configuration data is obtained; Perform PI parameter calculation on the control compensation signal according to the master-slave branch configuration data to obtain PI control parameters; Calculate the deviation between the real-time current and the average current of each parallel branch, input the PI control parameter into the current sharing controller, and obtain the PWM duty cycle compensation value; Performing overcurrent protection judgment on the parallel branch according to the PWM duty cycle compensation value to obtain an overcurrent protection instruction; The overcurrent protection instruction is input into the power regulating unit to regulate the output power of the yacht energy storage battery to obtain a power regulating signal, and a current sharing compensation calculation is performed on the power regulating signal to obtain a current sharing control signal.

8. A yacht energy storage battery internal short circuit detection device, characterized in that: Used to perform the yacht energy storage battery internal short circuit detection method according to any one of claims 1 to 7, the yacht energy storage battery internal short circuit detection device comprises: The sampling module is used to sample the voltage and current of the yacht energy storage battery pack to obtain the original sampling data; A parameter identification module, used for inputting the original sampling data into a three-level RC parallel network model for parameter identification to obtain RC network dynamic response data; A decomposition module, used for performing sliding window Fourier transform and wavelet packet decomposition on the RC network dynamic response data and the original sampling data to obtain a target feature vector; A judgment module, used to perform voltage mutation feature judgment, current mutation feature judgment and impedance spectrum feature judgment based on the target feature vector to obtain a multi-level fault judgment result; A control compensation module, used to start a three-loop nested control structure according to the multi-level fault judgment result, input the calculation results of current tracking control, power balance control and state protection control into a PWM modulation unit, and obtain a control compensation signal; The current sharing control module is used to input the control compensation signal into the current sharing controller, adjust the PWM duty cycle of the parallel branch, and obtain the current sharing control signal.

9. A computer device, characterized in that: It comprises a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and is characterized in that when the processor executes the computer program, the internal short circuit detection method of the yacht energy storage battery described in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the processor is enabled to execute the method for detecting internal short circuit of a yacht energy storage battery according to any one of claims 1 to 7.

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